Amazon Technologies, Inc.

Rishabh Jain

Vaibhav Jain

Akshat Vig

Amit Gupta

Somasundaram Perianayagam

Alexander Richard Keyes

James Christopher Sorenson

Nathan Pellegrom Riley

Stefano Stefani

Douglas Brian Terry

Lewis Bruck

Tate Andrew Certain

Akhilesh Mritunjai

Ming-Chuan Wu

Almero Gouws

Derek William Richard Chen-Becker

Tony Petrossian

Benjamin Donald Wood

Palak Agrawal

Sagar Mundra

Anshul Gupta

Jin Kyoung Kwon

A client of a distributed database service may conveniently enable replication of data from a source table to a destination (e.g., a different service/database table) by submitting a request enable replication for the source table. In response to the request to enable replication, the database service enables replication for the source table. To replicate a change, the database service may modify a format of the change based on a data storage format of the destination that is different than a data storage format of the database service. The database service monitors the performance of the replication and based on the performance, the database service may automatically modify the capacity to perform the replication of changes to the destination (e.g., by assigning additional resources to replication).

Replicating changes from a database to a destination and modifying replication capacity

Various embodiments are described regarding admitting for performance ordered operations of atomic transactions across a distributed database. In some embodiments, a node of a distributed system receives and accumulates requests for operations over a period of time. The node can then order the requests based on certain criteria, such as by timestamps of associated transactions. The node can then perform an admission control on the ordered requests, until a capacity of the node to perform the requests for operations is exceeded. During the admission control process, those requests for operations received within the period of time that are not admitted can be rejected by the node.

Admitting for performance ordered operations of atomic transactions across a distributed database

Non-relational database operations are invoked to provide results consistent with commands specified in a relational query language. A request to access data in a non-relational database is received that includes one or more commands specified in a query language for accessing data according to a relational data scheme. The request may be evaluated to determine one or more Application Programming Interfaces (APIs) to invoke operations at the non-relational database that provide a result consistent with the commands specified in the query language. The determined APIs are executed and a result returned for the request based on the execution of the APIs.

Invoking supported non-relational database operations to provide results consistent with commands specified in a relational query language

A request to perform a batch of operations is provided to a distributed database. The request comprises instructions for validating a condition. An association between the request and a unique identifier is stored. An item in the distributed database is locked and the condition is validated. The system that initiates processing of the batch of operations. A second request, comprising the identifier, is received. The second request is responded to by providing information indicative of the status of processing the first request, based on the stored association. The lock is released when processing of the first request has completed.

Idempotent transaction requests

A distributed database maintains a table on a first plurality of partitions. A request to restore the table to a point-in-time is received. The database determines, based on log data of the partitions, a maximum version number of an operation processed by the partitions. The log data is processed to exclude, from the restoration, operations whose transactions were started after the point-in-time, by setting the version number of those operations to be greater than the maximum version number. The log data is then applied to a second plurality of partitions, where the version number of each applied operation is less than or equal to the determined maximum version number.

Transactionally consistent point-in-time restore

A distributed database system maintains data for a logical table by storing, on a plurality of storage nodes, a collection of key-item pairs. An operation to delete a range of these items is processed by first storing, on each of the plurality of storage nodes, a tombstone record indicative of the items to be deleted. The tombstones are committed once each of the plurality of nodes has stored the tombstone. Items within the range are treated as deleted. A cleanup operation deletes items within the range and updates the tombstone.

Range deletes on a distributed database

Transaction operations may be graphed in order to determine performance compliance of transactions. An event to analyze transactions may be detected. Transactions to analyze for the event may be identified and a description of transaction operations for the identified transactions may be obtained. A graph of the transaction operations may be generated to indicate the dependencies between transactions and an evaluation of the graph may be performed to determine whether the transactions were performed with serializable isolation.

Graphing transaction operations for transaction compliance analysis

Transaction requests may be ordered in a distributed database according to an independently assigned sequence. Different distributed system nodes, such as a transaction coordinator and a storage node may independently assign sequence numbers to requests to access a distributed database. A storage node may receive the request from a transaction coordinator with an assigned sequence number and another request to which the storage node may assign a sequence number. The storage node can then order performance of the requests based on the sequence numbers.

Ordering transaction requests in a distributed database according to an independently assigned sequence

Updates performed as part of transaction requests to a data store may be included in a stream of updates. Updates to items in the data store that are included in transactions determined not to be committed to the data store may be excluded from the stream of updates. Records in the stream of updates may include an identifier for the transaction that included the update described by the record. The identifier for the transaction may be used to identify updates to other items in the data store that are included in the same transaction.

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Seattle, WA, United States of America

Rishabh Jain